Biomedical subjects

Chih-Jian Lih

Publications and source records attributed to Chih-Jian Lih.

5 recordsLinked to original sources

PubMed2006

Txr1: a transcriptional regulator of thrombospondin-1 that modulates cellular sensitivity to taxanes.

Using transcripts initiated at a chromosomally integrated retrovirus-based promoter to perturb gene expression randomly in human prostate cancer cells, we isolated cell clones resistant to taxane lethality and discovered the role of a previously uncharacterized gene, txr1, in this phenotype. We show that txr1 impedes taxane-induced apoptosis in tumor cells by transcriptionally down-regulating the production of thrombospondin-1 (TSP-1)--known earlier for both its anti-angiogenic and proapoptotic actions. Decrease of Txr1 or treatment with TSP-1 or TSP-1 mimetic peptide sensitized cells to taxane cytotoxicity by activating signaling through the CD47 receptor (also known as the integrin-associated protein), whereas interference with CD47 function reduced taxane-induced cell death. Cellular abundance of Txr1 and TSP-1 varied inversely, and alteration of the level of both proteins correlated highly with taxol resistance in 13 of 19 NCI-60 cancer cell lines. Our results reveal a hitherto unsuspected mechanism of taxane resistance, elucidate the role of txr1 in this resistance, and identify txr1 as a regulator of TSP-1 production and an agent for its chemotherapeutic modulation.

Antineoplastic Agents↗

PubMed2005

Effects of threshold choice on biological conclusions reached during analysis of gene expression by DNA microarrays.

Global analysis of gene expression by using DNA microarrays is employed increasingly to search for differences in biological properties between normal and diseased tissue. In such studies, expression that deviates from defined thresholds commonly is used for creating genetic signatures that characterize disease vs. normality. Although it is axiomatic that the threshold parameters applied to microarray analysis will alter the contents of such genetic signatures, the extent to which threshold choice can affect the fundamental conclusions made from microarray-based studies has not been elucidated. We used GABRIEL (Genetic Analysis By Rules Incorporating Expert Logic), a platform of knowledge-based algorithms for the global analysis of gene expression, together with conventional statistical approaches, to examine the sensitivity of conclusions to threshold choice in recently published microarray-based studies. An analysis of the effects of threshold decisions in one of these studies [Ramaswamy, S., Ross, K. N., Lander, E. S. & Golub, T. R. (2003) Nat. Genet. 33, 49-54], which arrived at the important conclusion that the metastatic potential of primary tumors is encoded by the bulk of cells in the tumor, is the focus of this article. We discovered that support for this conclusion highly depends on the threshold used to create gene expression signatures. We also found that threshold choice dramatically affected the gene function categories represented nonrandomly in signatures. Our results suggest that the robustness of biological conclusions made by using microarray analysis should be routinely assessed by examining the validity of the conclusions by using a range of threshold parameters.

Adenocarcinoma↗

PubMed2005

An integrated data analysis approach to characterize genes highly expressed in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the major causes of cancer deaths worldwide. New diagnostic and therapeutic options are needed for more effective and early detection and treatment of this malignancy. We identified 703 genes that are highly expressed in HCC using DNA microarrays, and further characterized them in order to uncover novel tumor markers, oncogenes, and therapeutic targets for HCC. Using Gene Ontology annotations, genes with functions related to cell proliferation and cell cycle, chromatin, repair, and transcription were found to be significantly enriched in this list of highly expressed genes. We also identified a set of genes that encode secreted (e.g. GPC3, LCN2, and DKK1) or membrane-bound proteins (e.g. GPC3, IGSF1, and PSK-1), which may be attractive candidates for the diagnosis of HCC. A significant enrichment of genes highly expressed in HCC was found on chromosomes 1q, 6p, 8q, and 20q, and we also identified chromosomal clusters of genes highly expressed in HCC. The microarray analyses were validated by RT-PCR and PCR. This approach of integrating other biological information with gene expression in the analysis helps select aberrantly expressed genes in HCC that may be further studied for their diagnostic or therapeutic utility.

Biomarkers, Tumor↗

PubMed2005

Cross-regulation among disparate antibiotic biosynthetic pathways of Streptomyces coelicolor.

A complex programme of regulation governs gene expression during development of the morphologically and biochemically complex eubacterial genus Streptomyces. Earlier work has suggested a model in which 'higher level' pleiotropic regulators activate 'pathway-specific' regulators located within chromosomal gene clusters encoding biosynthesis of individual antibiotics. We used mutational analysis and adventitious overexpression of key Streptomyces coelicolor regulators to investigate functional interactions among them. We report here that cluster-situated regulators (CSRs) thought to be pathway-specific can also control other antibiotic biosynthetic gene clusters, and thus have pleiotropic actions. Surprisingly, we also find that CSRs exhibit growth-phase-dependent control over afsR2/afsS, a 'higher level' pleiotropic regulatory locus not located within any of the chromosomal gene clusters it targets, and further demonstrate that cross-regulation by CSRs is modulated globally and differentially during the S. coelicolor growth cycle by the RNaseIII homologue AbsB. Our results, which reveal a network of functional interactions among regulators that govern production of antibiotics and other secondary metabolites in S. coelicolor, suggest that revision of the currently prevalent view of higher-level versus pathway-specific regulation of secondary metabolism in Streptomyces species is warranted.

Anti-Bacterial Agents↗

PubMed2002

Analysis of DNA microarrays using algorithms that employ rule-based expert knowledge.

The ability to investigate the transcription of thousands of genes concurrently by using DNA microarrays offers both major scientific opportunities and significant analytical challenges. Here we describe GABRIEL, a rule-based system of computer programs designed to apply domain-specific and procedural knowledge systematically and uniformly for the analysis and interpretation of data from DNA microarrays. GABRIEL'S problem-solving rules direct stereotypical tasks, whereas domain-specific knowledge pertains to gene functions and relationships or to experimental conditions. Additionally, GABRIEL can learn novel rules through genetic algorithms, which define patterns that best match the data being analyzed and can identify groupings in gene expression profiles preordered by chromosomal position or by a nonsupervised algorithm such as hierarchical clustering. GABRIEL subsystems explain the logic that underlies conclusions and provide a graphical interface and interactive platform for the acquisition of new knowledge. The present report compares GABRIEL'S output with published findings in which expert knowledge has been applied post hoc to microarray groupings generated by hierarchical clustering.

Algorithms↗